{"id":"W2012986875","doi":"10.1118/1.2756939","title":"Quantitative characterization of metastatic disease in the spine. Part II. Histogram‐based analyses","year":2007,"lang":"en","type":"article","venue":"Medical Physics","topic":"Management of metastatic bone disease","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Medicine; Voxel; Radiology; Bone disease; Histogram; Nuclear medicine; Medical imaging; Radiography; Pathology; Osteoporosis; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001133484,0.0001423292,0.0003390381,0.0001101946,0.00004266262,0.000006622,0.0001598782,0.00001880656,0.000265959],"category_scores_gemma":[0.001026754,0.00009573064,0.0001402203,0.000630778,0.0002126367,0.00006946572,0.00003215298,0.000164091,0.00001393658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000315626,"about_ca_system_score_gemma":0.0001774865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002424204,"about_ca_topic_score_gemma":0.000007103477,"domain_scores_codex":[0.9977464,0.0001256936,0.0004775384,0.0001984325,0.001228881,0.0002230168],"domain_scores_gemma":[0.9989765,0.0001580905,0.0001836046,0.0003397397,0.000088957,0.0002531641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01315521,0.09797798,0.1779788,0.01968682,0.004015016,0.01373475,0.01495435,0.0004936254,0.03800168,0.1742625,0.01926725,0.426472],"study_design_scores_gemma":[0.01178422,0.001486663,0.9187438,0.001644634,0.004363706,0.000003907701,0.001190074,0.03805001,0.005176209,0.00651064,0.01026696,0.0007791095],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8292665,0.0001316498,0.1648938,0.00399594,0.0001288159,0.0007220745,0.00003126349,0.00003311624,0.0007968688],"genre_scores_gemma":[0.9955221,0.00001355523,0.0008573308,0.002976118,0.00007481012,0.00002581991,0.0004213616,0.00001472138,0.0000941684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.740765,"threshold_uncertainty_score":0.3903782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0904440305940504,"score_gpt":0.3888858956261084,"score_spread":0.2984418650320579,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}